Image-driven structural steel damage condition assessment method using deep learning algorithm
Image-driven structural steel damage condition assessment method using deep learning algorithm is a scholarly work, published in 2019 in ''Measurement''. The main subjects of the publication include finite element method, convolutional neural network, visualization, parametric statistics, deep learning, artificial intelligence, Pavement management, artificial neural network, fuse, structural engineering, feature, fatigue, pattern recognition, computer science, and engineering. The paper presents a deep learning based structural steel damage condition assessment method that uses images for post-hazard inspection of ultra-low cycle fatigue induced damage in structural steel fuse members.